Many Roads to Rome
Massachusetts General Hospital
2025-10-17
Traditional Approach:
The Question: > “Who will have an event in the next 10 years?”
What’s Missing:
Better Question: > “What is their lifetime burden, and when should we intervene?”
Key Insight
Traditional risk models assume one pathway. Reality is far more complex—different trajectories require different intervention strategies.
Clinical Profile:
Research Evidence:
Your Model Findings:
Signatures change 5-10 years before clinical diagnosis
Progression Path:
Key Research Finding:
Urbut et al., medRxiv 2024: > “Metabolic signature (Sig 12) rises first, cardiovascular signature (Sig 5) follows 2-3 years later”
The Intervention Window: - When metabolic signature plateaus - But CVD signature accelerates - 2-3 years before clinical CAD
Signature Transition:
Clinical Picture:
Your Research:
Evidence Base:
Signature Behavior:
Often missed: Normal lipids but high inflammatory burden
Characteristics:
Model Performance:
Key Question: What distinguishes this group? Can we replicate their trajectory in others?
Clinical Impact
Same 10-year risk ≠ Same intervention. Trajectory determines timing and intensity of prevention.
What It Does:
What It Incorporates:
Scale:
Mathematical Framework:
\[\pi_{i,d,t} = \kappa \times \sum_k \theta_{i,k,t} \times \phi_{k,d,t}\]
Where:
Key Innovation:
Signature velocity (rate of change) predicts risk:
Important
“Top quartile Sig 5 velocity has HR=2.8 for CAD”
This translates to 18 months earlier CAD onset
Traditional Approach:
Life Course Approach:
Your Discovery:
“Fast signature progression → higher disease risk independent of absolute level”
Clinical Translation:
Two 55-year-old women, both with 10-year ASCVD risk of 7.5%:
| Feature | Woman A | Woman B |
|---|---|---|
| LDL trajectory | Stable 130 mg/dL × 20 years | 120→180 mg/dL over 15 years |
| Inflammation | Recent hsCRP uptick (1→4 mg/L) | Stable CRP < 2 mg/L |
| Signature pattern | Inflammatory sig rising | Metabolic sig dominant |
| PCE risk | 7.5% | 7.5% |
Both receive identical recommendations:
Different strategies based on trajectories:
Woman A (Inflammatory):
Woman B (Metabolic):
Current Guidelines:
Life Course Approach:
Evidence:
Implementation:
Current Approach:
Life Course Approach:
Your Data:
Interventions:
Current Gap:
Life Course Approach:
Your Finding:
Treatment Considerations:
Learn from Success:
Research Needed:
Clinical Application:
Clinical Barriers:
Payer Barriers:
Communication Challenges:
Key Question for Discussion
What’s the threshold for payer coverage of preventive therapies in otherwise “healthy” high-lifetime-risk patients?
Current State:
LIVE-CVD Model:
SCOT-HEART Trial:
Your Model (Aladynoulli):
Emerging Tools:
AI-Enhanced Imaging:
Polygenic Risk Scores:
EHR Integration:
Wearables & Sensors:
The Goal
Tailor prevention to individual life course trajectories—not one-size-fits-all based on 10-year risk alone.
The Problem:
The Solution:
The Evidence:
The Tools:
The Challenges:
The Path Forward:
Contact:
Sarah Urbut, MD PhD Massachusetts General Hospital surbut@mgh.harvard.edu
Preprint:
Urbut et al., medRxiv 2024 doi: 10.1101/2024.09.29.24314557
Code:
Key Collaborators:
Questions for Discussion:
Ready for Discussion
Let’s explore how we can move from theory to practice in the critical decades.
Mathematical Framework:
Disease probability at time \(t\): \[\pi_{i,d,t} = \kappa \times \sum_{k=1}^K \theta_{i,k,t} \times \phi_{k,d,t}\]
Components:
Innovation:
UK Biobank (Primary):
Cross-Cohort Validation:
Robustness:
Heart House Roundtable | Session 2